This invention relates generally to data compression techniques and more particularly to adaptive differential pulse code modulation (ADPCM) compression of data.
As is known in the art, one of the demanding applications in digital signal processing involves the efficient transmission and storage of data corresponding to information having a relatively high degree of redundancy. For example, advances in computer technology for mass storage and digital processing have fostered the development of digital processing of image data, speech data, telemetry data, and so forth. However, the large amount of data used in such digital processing has increased the need for implementing advanced data compression techniques to remove redundancy from the data and thus improve efficiency of transmission and/or storage of such data.
In particular, one application of digital processing of large quantities of data is that data relating to image data and, in particular, image data which is obtained through processing of sonar signals. In general, image data and, in particular, sonar image data is characterized as having a high degree of redundancy, or put another way, is characterized as being relatively predictable and smooth. For example, for most sonar image data sets, much of the data is "noise only data" and thus rapid changes in the data are relatively infrequent and smooth.
A technique used to reduce the amount of data used to represent an input data stream (i.e. to compress the data) is the so-called "adaptive differential pulse code modulation technique" (ADPCM).
ADPCM processing involves partitioning input data into data sequences of data groups or data blocks to be analyzed and adaptively characterizing such data by computation of linear prediction parameters for each data block analyzed. These linear prediction parameters include quantized prediction coefficients and a quantized prediction error sequence. In the quantized prediction error sequence a fixed number of bits is used to represent the prediction error associated with said prediction error sample in the quantized prediction error sequence. The ultimate goal of ADPCM compression is to obtain a high compression ratio (i.e. a ratio of the number of original bits in the input data is the number of bits in the compressed data) without a significant increase in distortion imparted to data reconstructed from the ADPCM parameters.
A problem often occurs with an ADPCM data compressor operating at high compression ratios. At high compression ratios, that is, at a high ratio of input data bits to output data bits reconstruction of the input data from the ADPCM parameters for all data blocks produces on average acceptable performance. However, some individual blocks may have an unacceptable performance as measured by an error signal or distortion level if the blocks contain data that are substantially different than the typical data encountered during compression of the blocks. For image data, this might result from an occurrence of an isolated bright spot in the image frame which introduces a rapid increase in intensity in the data and could, for example, be related to a object or target identified by a sonar system.
One technique which could be used to compensate for errors induced by rapid transitions in the data would be to increase for each block of data the number of bits used to represent the prediction error sequence. One drawback of increasing the number of bits used to represent the prediction error is that the compression ratio is significantly decreased and as a result the performance of the ADPCM technique as a compressor of data is degraded.